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嗅觉受体神经元产生多种反应模式,增加了编码空间的维度。

Olfactory receptor neurons generate multiple response motifs, increasing coding space dimensionality.

机构信息

Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, United States.

Brown University - National Institutes of Health Graduate Partnership Program, Providence, United States.

出版信息

Elife. 2023 Jan 31;12:e79152. doi: 10.7554/eLife.79152.

DOI:10.7554/eLife.79152
PMID:36719272
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9925048/
Abstract

Odorants binding to olfactory receptor neurons (ORNs) trigger bursts of action potentials, providing the brain with its only experience of the olfactory environment. Our recordings made in vivo from locust ORNs showed that odor-elicited firing patterns comprise four distinct response motifs, each defined by a reliable temporal profile. Different odorants could elicit different response motifs from a given ORN, a property we term motif switching. Further, each motif undergoes its own form of sensory adaptation when activated by repeated plume-like odor pulses. A computational model constrained by our recordings revealed that organizing responses into multiple motifs provides substantial benefits for classifying odors and processing complex odor plumes: each motif contributes uniquely to encode the plume's composition and structure. Multiple motifs and motif switching further improve odor classification by expanding coding dimensionality. Our model demonstrated that these response features could provide benefits for olfactory navigation, including determining the distance to an odor source.

摘要

气味与嗅觉受体神经元 (ORNs) 结合会引发一连串的动作电位,为大脑提供其对嗅觉环境的唯一体验。我们在活体蝗虫 ORNs 上的记录表明,气味诱发的放电模式包含四个不同的反应模式,每个模式都有可靠的时间特征。不同的气味可以从给定的 ORN 中引发不同的反应模式,我们称之为模式切换。此外,当重复出现类羽状气味脉冲时,每种模式都会经历自身形式的感觉适应。一个受我们的记录约束的计算模型表明,将反应组织成多个模式为对气味进行分类和处理复杂的气味羽流提供了实质性的好处:每个模式都独特地有助于编码羽流的组成和结构。多个模式和模式切换通过扩展编码维度进一步提高了气味分类。我们的模型表明,这些反应特征可以为嗅觉导航提供优势,包括确定与气味源的距离。

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